Much like the cloud, technologists will continue to reinvent machine learning until it will likely look completely different than it does now.

IBM in particular has recently closed down less progressive and lucrative endeavors to make room for all the things big-data-empowered machine learning makes possible. This is a long way from Watson, its machine-intelligence-as-a-service platform.

Most agree that machine learning must be open source from now on. This may seem obvious to some, but such things aren’t always obvious to those on the outside.

With machine learning, all algorithms are best when open by default. It not only makes the work easier to check, it means products that use the algorithms have more transparency about what they’re doing. And it puts the emphasis where it beongs – on the data and on the data sources.

Melody K. Smith

Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.